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The idea of Artificial Intelligence (AI) often conjures up ideas related to science fiction or of an individual mashing the keyboard, working on some complex algorithm. But regardless, we typically have strong preconceived notions of how we view it, especially in relation to education curriculums. However, we hope to challenge some of these notions and highlight potential areas in which AI could be adopted into different areas of an education curriculum.

For our purposes, we borrow Mozilla’s definition of AI that “includes everything from algorithms and automation to complex, responsive machine learning systems and the social actors involved in maintaining those systems.” Our Educational Toolkit encompasses all aspects of curricula, to make students feel welcome in the AI space. The following list breaks down different subject areas and where/how AI could intersect with them. 

  • Computer Science/Technology – This seems like the most obvious area in which students learn how to construct AI by writing code. While this subject area also investigates the “why” of using AI, computer science tends to explore the “how” of creating AI more than other subject areas.
  • Math – Similar to computer science, math plays an integral role in computer science as well as in the construction of AI. More specifically, mathematics such as algebra, calculus and probability are core to machine learning, which forms the foundation through which artificial intelligence functions.
  • History/Social Studies/Governance – AI can be incorporated within social studies by analyzing how it is used and how it impacts various social structures. For instance, teachers could examine AI through social media and how that affects ideologies, public policies, or public perceptions to name a few.
  • Economics – Similar to social studies, economics could investigate how AI is created and implemented in ways that shape our practice of economics. This could include looking at how AI is being used to rank job applications, make loan decisions, determine who qualifies for health insurance, among other economic topics. 
  • English/Foreign Languages – AI is being used to help individuals write in their own language (e.g., Grammarly) as well as learn and/or communicate in other languages too (e.g., Google Translate, Duolingo). Additionally, AI has been used to help research different types of literature, searching for common themes within works, examining language for common patterns or structures, or compiling literature reviews. 
  • Creative Writing – Just as AI is being used to research writing, it has also been taught to produce its own writing based on machine learning of other creative works. In addition to the coding of AI, programmers who work on these types of projects often incorporate aspects of creative writing to guide elements of AI, such as in the construction of AI powered assistants.
  • Arts – AI is also being created to create art ranging from musical compositions to visual designs. Likewise, the underlying nature of AI has been used to further explore concepts behind musical theory and artistic analysis and techniques in the classroom. 

While these descriptions are merely scratching the surface of AI and how it intersects with different curricula, our main takeaway is that AI merits more attention within formal education systems. In particular, the idea or question of trust and ethics links the role of AI among all educational subjects, and AI will continue to impact and shape important topics of privacy, race, gender, class, education, ideology, among many others. Consequently, we should be aware of how vital it is to address AI in the classroom and adopt it in a manner that best serves all students, so one day every student can feel that AI is for them too. 

– Andrew Virtue

Trustworthy AI Toolkit working group